def test_variance_ratio_non_robust(self):
vr = VarianceRatio(self.inflation, robust=False, debiased=False)
y = self.inflation
dy = np.diff(y)
mu = dy.mean()
dy2 = y[2:] - y[:-2]
nq = dy.shape[0]
denom = np.sum((dy - mu) ** 2.0) / nq
num = np.sum((dy2 - 2 * mu) ** 2.0) / (nq * 2)
ratio = num / denom
variance = 3.0 / 2.0
stat = np.sqrt(nq) * (ratio - 1) / np.sqrt(variance)
assert_almost_equal(stat, vr.stat)
orig_stat = vr.stat
vr.robust = True
assert_equal(vr.robust, True)
assert vr.stat != orig_stat
def test_variance_ratio_non_robust(self):
vr = VarianceRatio(self.inflation, robust=False, debiased=False)
y = self.inflation
dy = np.diff(y)
mu = dy.mean()
dy2 = y[2:] - y[:-2]
nq = dy.shape[0]
denom = np.sum((dy - mu) ** 2.0) / nq
num = np.sum((dy2 - 2 * mu) ** 2.0) / (nq * 2)
ratio = num / denom
variance = 3.0 / 2.0
stat = np.sqrt(nq) * (ratio - 1) / np.sqrt(variance)
assert_almost_equal(stat, vr.stat)
orig_stat = vr.stat
vr.robust = True
assert_equal(vr.robust, True)
assert vr.stat != orig_stat
